CN102685511A - Image processing apparatus and image processing method - Google Patents
Image processing apparatus and image processing method Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/10—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths
- H04N23/12—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths with one sensor only
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
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- H04N1/46—Colour picture communication systems
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- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise
- H04N25/61—Noise processing, e.g. detecting, correcting, reducing or removing noise the noise originating only from the lens unit, e.g. flare, shading, vignetting or "cos4"
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Abstract
The invention relates to an image processing apparatus and an imaging processing method. The image processing apparatus comprises an edge detection means (50) for detecting edges from image data, an on-axis chromatic aberration edge detection means (51) for detecting an edge determined to include chromatic aberration on an axis from the edges,a color deviation amount acquisition means (60) for acquiring color deviation amounts on the edges, and a correction means (70) for performing chromatic aberration correction, wherein the on-axis chromatic aberration edge detection means detects, as the edge which includes the chromatic aberration on the axis, an edge having signals corresponding to at least one color on the edge of the image data, which has a blur amount that is not less than a threshold value, and signals corresponding to at least another color which has a blur amount that is less than the threshold value, and the color deviation amount acquisition means acquires the color deviation amounts from edges among the edges.
Description
Technical field
The present invention relates to be used to carry out the technology that the chromatic aberation of image is proofreaied and correct.
Background technology
The picture pick-up device that utilizes pick-up lens such as digital camera etc. is used for various uses.The light beam that passes pick-up lens has refractive index in pick-up lens, this refractive index changes according to the wavelength of light beam.Therefore, even taken the photograph in the light that body reflects same, the distance of the optical axis center of the light beam that is comprised in the reverberation from the image space on the imageing sensor to the imageing sensor is also according to the wavelength of these light beams and difference.This multiplying power chromatic aberation generates misalignment, promptly by the variation of the image space of each seperate color, thereby in image, generate and under normal circumstances taken the photograph non-existent color on the body, cause quality to descend thus.
Because the pixel count of employed imageing sensor increases year by year, and the unit picture element size reduces, so even seldom problematic multiplying power chromatic aberation also becomes obvious in conventional art.As the technology of proofreading and correct this chromatic aberation through image processing, proposed a kind of being used for from image acquisition misalignment amount to compensate the technology of this misalignment amount.
For example, TOHKEMY 2000-299874 and 2006-020275 disclose following technology.At first; Part goes up below the repetition and handles on the edge of: after move with respect to the position of the view data that is formed by other color component the position of the view data that is formed by a color component, obtain the summation of the difference of the signal level between the color component in each pixel.The position of the view data that acquisition is formed by a color component when the summation of the difference of the signal level between the color component minimizes is with respect to the amount of movement of the position of the view data that is formed by other color component, to obtain to make the minimized correcting value of misalignment amount.
Yet; The summation of the difference of signal level is obtained in the method for correcting value between above-mentioned use color component; Not only generate the multiplying power chromatic aberation also generate by axle on the fuzzy marginal portion that causes of chromatic aberation, often can not obtain accurate correcting value to the misalignment that causes by the multiplying power chromatic aberation.
Fig. 9 A is illustrated in the variation that the generation axle is gone up the signal level of the view data of the color component of red (R), green (G) and blueness (B) in the part of chromatic aberation.With reference to figure 9A, because axle is gone up a chromatic aberation, the correlation between the view data of the view data of B color component and G (or R) color component is lower than the correlation between the view data of the view data of R color component and G color component.This be because, compare with the part that only generates the multiplying power hue difference, in the part of chromatic aberation, the correlation between the view data of particular color composition and the view data of all the other color components is low on generating axle.
Therefore, when the marginal portion of chromatic aberation used said method to obtain correcting value on comprising axle, the form and aspect of marginal portion possibly change before and after proofreading and correct.
Fig. 9 B illustrates following state: on generating axle, in the part of chromatic aberation, use the summation of the difference of the signal level between the color component to obtain correcting value, and use this correcting value to proofread and correct.For example; Shown in Fig. 9 A; Suppose that the G plane as the view data that is formed by the G color component does not have misalignment with the R plane that is used as the view data that is formed by the R color component, and the G plane has misalignment with the B plane that is used as the view data that is formed by the B color component.For the difference of the signal level between the color component that makes B plane and G (or R) plane minimizes, will be at the signal level on the B plane than mixing each other than zone high on the B plane in zone high on the G plane and the signal level on the G plane.Especially, when the correlation on the plane of B plane and all the other color components is low, there is the big zone of difference of the signal level between B and the G plane.For example; With the corresponding part of dash area among Fig. 9 A be yellow; But because exaggerated correction, with Fig. 9 B in the corresponding part of dash area be other color, promptly blue, so between the form and aspect of the marginal portion before and after proofreading and correct relatively the time, the observer feels very discomfort.Can use the method that reduces observer's sense of discomfort through the form and aspect of the marginal portion after the adjustment correction, but this possibly destroy the original color structure of being taken the photograph body.
Summary of the invention
Consider that the problems referred to above make the present invention, and the present invention keeps the possibility of the exaggerated correction lower than conventional method can be through chromatic aberation on utilizing the image processing axis calibration time, proofread and correct the multiplying power chromatic aberation effectively.
According to a first aspect of the invention, a kind of image processing equipment comprises: edge detection unit is used for from by detecting the edge with the formed view data of the corresponding signal of multiple color; Chromatic aberation edge detection unit on the axle is used for being judged as the edge that comprises a last chromatic aberation from the detection of said edge; Misalignment amount acquiring unit is used to obtain the misalignment amount on the edge; And correcting unit; Be used to use correcting value to carry out the chromatic aberation correction based on said misalignment amount; Wherein, It is to comprise that said axle goes up the edge of chromatic aberation with following rim detection that said axle is gone up the chromatic aberation edge detection unit: have the fuzzy quantity of the threshold value of being not less than with the corresponding signal of at least a color on this edge of said view data; And have fuzzy quantity with the corresponding signal of another kind of at least color on this edge of said view data less than said threshold value, and said misalignment amount acquiring unit from by the detected edge of said edge detection unit, with go up different edge, the detected edge of chromatic aberation edge detection unit by said axle and obtain said misalignment amount.
According to a second aspect of the invention, a kind of image processing method may further comprise the steps: use edge detection unit from by detecting the edge with the formed view data of the corresponding signal of multiple color; The chromatic aberation edge detection unit that goes up the use axle detects from said edge and is judged as the edge that comprises a last chromatic aberation; Use misalignment amount acquiring unit to obtain the misalignment amount on the edge; And use the correcting unit utilization to carry out chromatic aberation and proofread and correct based on the correcting value of said misalignment amount; Wherein, It is to comprise that said axle goes up the edge of chromatic aberation with following rim detection that said axle is gone up the chromatic aberation edge detection unit: have the fuzzy quantity of the threshold value of being not less than with the corresponding signal of at least a color on this edge of said view data; And have fuzzy quantity with the corresponding signal of another kind of at least color on this edge of said view data less than said threshold value, and said misalignment amount acquiring unit from by the detected edge of said edge detection unit, with go up different edge, the detected edge of chromatic aberation edge detection unit by said axle and obtain said misalignment amount.
Through below with reference to the explanation of accompanying drawing to exemplary embodiments, it is obvious that further feature of the present invention will become.
Description of drawings
Fig. 1 is the block diagram that illustrates according to the image processing equipment of the embodiment of the invention;
Fig. 2 illustrates the flow chart of utilization according to the processing of the image processing equipment of embodiment;
Fig. 3 A and 3B illustrate the zone cut apart to each picture altitude and the figure of correction data;
Fig. 4 is the flow chart that multiplying power chromatic aberation treatment for correcting and the processing of axle colouring aberration correction are shown;
Fig. 5 A, 5B and 5C be method that the fuzzy quantity that a last chromatic aberation is set is shown, be used to generate the figure of the example of fuzzy chart and captured image;
Fig. 6 A, 6B and 6C are the tables that axle colouring aberration information table is shown;
Fig. 7 A and 7B are the figure that the relation between edge and the fuzzy quantity is shown;
Fig. 8 is the figure that the gradient and the relation between the fuzzy quantity at edge are shown; And
Fig. 9 A and 9B are the figure that the misalignment of marginal portion is shown.
Embodiment
Below embodiments of the invention will be described.Even in following explanation, do not mention the object planes of color especially, also can use following method to carry out the correction of the misalignment between G and the R plane and the correction of the misalignment between G and the B plane equally.
And; Although use the image processing equipment comprise such as the camera system of digital camera etc. in the present embodiment, the present invention can be applicable to by such as the captured view data that is formed by a plurality of planes of color such as the camera system of the use pick-up lens of digital camera etc.Therefore, object images according to the present invention is not limited to the jpeg data after RAW data and video picture are handled.Can also use after image processing equipment except that digital camera reads the captured view data of digital camera for example, the use image processing equipment is realized the present invention.Therefore, according to image processing equipment of the present invention and the nonessential pick-up lens that comprises.
Handle general introduction below at first will explaining: the image processing equipment that carries out the correction of multiplying power chromatic aberation generates multiplying power chromatic aberation correction data from image, and correcting image.
Fig. 1 is the block diagram that illustrates according to the image processing equipment of the embodiment of the invention.Image processing equipment comprises image pickup optical system 10, imageing sensor 20, A/D converting unit 30, color separated unit 40, comprises an edge extracting unit 50 of last chromatic aberation edge extracting unit (chromatic aberation edge detection unit on the axle) 51, multiplying power chromatic aberation correction data generation unit 60, multiplying power chromatic aberation correcting unit 70, axle colouring aberration correction unit 110, control unit 80, memory 90 and I/F 100.
With reference to figure 1, pass image pickup optical system 10 from the light of being taken the photograph body, and on imageing sensor 20, form image, imageing sensor 20 is used for being carried out opto-electronic conversion by subject image.Imageing sensor 20 is the single panel color image transducers that comprise general primary-color filter.Primary-color filter comprise have 650nm, near three types color filter of the main passband 550nm and the 450nm, and take with red (R), green (G) and blueness (B) respectively with corresponding planes of color (generation is by the view data that forms with the corresponding signal of multiple color).In the single panel color image transducer, can only spatially arrange the color filter of these types, and in each pixel, obtain the luminous intensity on each planes of color to each pixel.Therefore, the colored mosaic image data of imageing sensor 20 outputs.
A/D converting unit 30 will become to be suitable for the numerical data of successive image processing from imageing sensor as the colored mosaic image data transaction of aanalogvoltage output.The 40 pairs of colored mosaic image data in color separated unit are carried out interpolation to be created on the color image data that has R, G and B colouring information in all pixels.
Although in the wide region like the described complicated approach of document " E.Chang, S.Cheung, and D.Pan; ' Color filter array recovery using a threshold-based variable number of gradients; ' Proc.SPIE, vol.3650, pp.36-43; Jan.1999 ", proposing the various interpolation methods that are used for this interpolation from simple linear interpolation, the present invention does not limit interpolation method.
Comprise that a color image data that the edge extracting unit 50 of last chromatic aberation edge extracting unit 51 is generated from color separated unit 40 detects edge (marginal portion).Based on detected marginal information, multiplying power chromatic aberation correction data generation unit 60 generates multiplying power chromatic aberation correction data from view data.Multiplying power chromatic aberation correcting unit 70 uses the multiplying power chromatic aberation correction data that is generated to carry out the multiplying power chromatic aberation and proofreaies and correct.With employed view data in each processing unit and such as the storage of shooting time information etc. in memory 90, and control unit 80 these processing units of control.And, according to related environment, will input to image processing equipment such as the peripheral operation of user indication etc. via I/F (interface) 100.
Fig. 2 illustrates the flow chart of utilization according to the multiplying power chromatic aberation correct operation of the image processing equipment of present embodiment, and illustrates through comprising a processing sequence that edge extracting unit 50, correction data generation unit 60 and the correcting unit 70 of last chromatic aberation edge extracting unit 51 carried out.Below will explain that utilization proofreaies and correct according to the multiplying power chromatic aberation that the image processing equipment of present embodiment carries out with reference to each step described in the figure 2.
At first, detect on the edge of among the step S101, detect obvious each edge that occurs of the misalignment that causes owing to the multiplying power chromatic aberation from view data.Y (brightness) plane is used for rim detection.In this case, the edge that detect is limited to pixel value from each edge that benchmark alters a great deal laterally, thereby obtains accurate misalignment amount, wherein, benchmark be assumed that with imageing sensor on the optical axis center consistent location.And, occur because the misalignment that the multiplying power chromatic aberation causes conduct is blured, thereby expect to have certain width so that the edge that the dullness of signal level increases or the dullness minimizing continues on a plurality of pixels is an object.
In misalignment amount obtaining step S102, detect on the edge of among the step S101 and obtain the misalignment amount on detected each edge.Although there are several methods of obtaining the misalignment amount, for example can using usually, said method obtains the misalignment amount.This means each marginal portion is repeated following processing: the position of moving a view data on the planes of color with respect to the position of the view data on other plane, and obtain the summation of the difference of the signal level between the color component.The position of the view data of a color component with the acquisition correcting value, thereby minimized the misalignment amount with respect to the amount of movement of the position of the view data of other color component when the summation of the difference of the signal level of acquisition between color component minimized.
In order to simplify processing, based on the relation of the position between optical centre and each edge, adopt here/lower direction, a left side/right-hand to, tiltedly upper right/tiltedly the lower left to or tiltedly upper left/tiltedly the lower right is to the direction as misalignment.
When R plane (or B plane) with respect to the G plane when optical centre squints, be negative value as the misalignment amount of the output among the misalignment amount obtaining step S102.Yet, when squint on the direction opposite with optical centre with respect to the G plane on R plane (or B plane), the misalignment measurer have on the occasion of.In this case, when obtaining the misalignment amount, measure the consistent degree on each plane and the method for estimated color departure when being employed in this plane of skew.Yet, at this moment, if given edge comprises a last chromatic aberation, the situation that the high point of consistent degree always is not used as the point of the misalignment that causes owing to the multiplying power chromatic aberation takes place, reduce the misalignment amount thus and obtained precision.Therefore, use the fuzzy quantity on R, G and B plane on each detected edge to carry out upward chromatic aberation evaluation of axle, and eliminating is be evaluated as the edge with last chromatic aberation.This makes the misalignment amount that can improve among the misalignment amount obtaining step S102 obtain precision.To be applied to the detection at the edge that comprises a last chromatic aberation according to the processing of present embodiment, and the back will specify and should handle with reference to figure 4.
Generate among the step S103 in correction data, the relation that obtains between picture altitude and the misalignment through the misalignment amount based on each edge that obtains among the picture altitude at detected each edge among the edge detecting step S101 and the misalignment amount obtaining step S102 generates correction data.Here the picture altitude of mentioning is meant from the distance of the locations of pixels on the optical axis that is positioned at pick-up lens (being designated hereinafter simply as optical centre) to interested pixel.
Below will specify the correction data generative process.
(1) the misalignment amount D that obtains to be obtained among the misalignment amount obtaining step S102 with respect to the misalignment of the picture altitude L at detected each edge among the edge detecting step S101 than M:
M＝D/L
(2) shown in Fig. 3 A, to each picture altitude view data is divided into 8 regional h1～h8, to select the zone that each edge belongs in the above-mentioned edge.
(3) carry out aforesaid operations (1) and (2) to detected a plurality of edges in the view data; To cut apart by each picture altitude each zone in 8 zones that obtain with misalignment than M addition; And obtain the mean value of misalignment to each zone, thereby confirm the misalignment ratio in each zone than M.
(4) shown in Fig. 3 B, from picture altitude and the misalignment that obtained than represents picture altitude and misalignment than between the multinomial approximate expression F of high-order (1) of relation, so that result of calculation is confirmed as correction data.Fig. 3 B illustrates the example that uses three rank polynomial computation correction datas.
Attention can be carried out rim detection to all edges in the view data and the misalignment amount is obtained.Yet; Misalignment that can be through for example in to each zone of cutting apart by each picture altitude in 8 zones that obtain, quantity being equal to or greater than predetermined threshold during than addition end edge detect with the misalignment amount and obtain raising treatment effeciency when keeping given reliability.
And, when only using when cutting apart the zone that detects respective edges in 8 zones that obtain by each picture altitude and calculate the multinomial approximate expression of high-order,, also can generate correction data even there is the zone that does not detect respective edges.
In aligning step S104, use correction data to generate the correction data that generates among the step S103 and come the correction of color deviation.That is, come the correction of color deviation through the position of moving the view data of at least one planes of color in a plurality of planes of color.
At first, pixel from each plane (R and B plane) that will proofread and correct (X, Y) picture altitude L obtain misalignment than M:
M＝F(L)
Note, use with the coordinate system of optical centre as (0,0).
Obtain below utilizing through misalignment proofread and correct the pixel that is generated coordinate position (X1, Y1):
X1＝X+M×X
Y1＝Y+M×Y
Generate on each plane that to proofread and correct and coordinate position (X1, the Y1) signal level of corresponding pixel, and this signal level confirmed as pixel (X, signal level Y) through interpolation processing the signal level weighting summation of surrounding pixel.Carrying out these computings to all pixels proofreaies and correct to carry out misalignment.
The processing general introduction that generates multiplying power chromatic aberation correction data and correcting image from image more than has been described.
Below will specify according to the multiplying power chromatic aberation correction of present embodiment and handle with an axle colouring aberration correction with reference to flow chart shown in Figure 4.
The rim detection of using the Y plane among the edge detecting step S201 at first is described.Generate the Y planed signal from the R, G and the B planed signal that are generated by color separated unit 40 at first.Generate the Y planed signal below using:
Y＝0.299R+0.587G+0.114B
Carry out rim detection in the plane to defined Y in this equality.Although can use several kinds of edge detection methods, use following method to detect in the present embodiment.Because the edge is the fast-changing part of signal level, thereby the differentiating of variation that is used to extract function can be used for rim detection.When using first derivative (gradient), with the denotation coordination position (x, the value of the first derivative of the gradient of the signal level of y) locating be expressed as vector G with size and Orientation (x, y)=(fx, fy), and through following calculating fx and fy:
The derivative of x direction: fx=f (x+1, y)-f (x, y)
The derivative of y direction: fy=f (x, y+1)-f (x, y)
Therefore, through following edge calculation intensity:
or | fx|+|fy|
Also use second dervative L (x, y) (Laplacian) edge calculation intensity:
L(x，y)＝|4·f(x，y)-{f(x，y-1)+f(x，y+1)+f(x-1，y)+f(x+1，y)}|
Have and the corresponding concentration of edge strength through using said method that the view data that rim detection obtained is carried out on the Y plane.In this case, predetermined threshold Th1 is set, and the pixel detection that will have greater than the signal value of threshold value Th1 is the edge.As the benchmark that threshold value Th1 is set, only need be provided with and can the chromatic aberation detection be the value of edge institute basis.
In step S202,, the fuzzy quantity Th2 of a last chromatic aberation is set for chromatic aberation from each detected rim detection axle.To specify step S202 with reference to figure 5A.
At first,, need prepare the fuzzy quantity information of chromatic aberation on the axle various imaging conditions under in advance with the form of table as prerequisite, and with this information stores on memory shown in Figure 1 90.Fuzzy below chromatic aberation generates on the axle: fuzzy amount is according to changing such as lens type, the various imaging conditions of being taken the photograph body distance (or pupil distance), F value and focal length etc.Therefore, shooting pattern under various imaging conditions, and measure the fuzzy quantity that is generated.Although can take any chart, can use the for example edge of the monochromatic chart shown in Fig. 5 B with high-contrast.Fig. 5 C illustrates the result's who takes the chart shown in Fig. 5 B example.When the generation axle is gone up chromatic aberation, shown in Fig. 5 C, generate fuzzy naturally.The fuzzy quantity of measurement on this edge.Shown in Fig. 6 A～6C, the tabulation of measuring the result of fuzzy quantity when changing imaging conditions in the same manner remains the table (table information) to each lens type and each imaging conditions.
Be back to Fig. 5 A again, at first, in step S301, from memory shown in Figure 1 90 obtain camera lens ID, F value, focal length and axle when taking the photograph body distance (or pupil distance), shooting gone up chromatic aberation fuzzy quantity table.In step S302, from axle, search the chromatic aberation fuzzy quantity table and the corresponding fuzzy quantity of imaging conditions.If imaging conditions is consistent with the table data transformation, then obtain fuzzy quantity through carrying out interpolation calculation from approximate data.In step S303, the fuzzy quantity that is obtained so that being converted to, this fuzzy quantity is generated fuzzy pixel count divided by pixel separation.At last, in step S304, the fuzzy pixel count that has after the conversion is set to fuzzy quantity Th2.Thus, the value that under each imaging conditions, changes is set to the fuzzy quantity Th2 as threshold value.
Go up chromatic aberation in order to continue to detect axle, in step S203, carry out the chromatic aberation evaluation to the edge that radially extends about optical centre from each detected edge.To specify step S203.Fig. 7 A illustrates R, G and B plane and the width of set fuzzy quantity Th2 on detected edge, this edge.Carrying out dullness increase/minimizing to the plane that has the highest signal level in the R in this fringe region, G and the B plane (being the B plane in this case) judges.Chromatic aberation has following characteristic: its signal level is assigned to dash area from high highlights and is gradually changed, that is, its signal level increases with dullness or the dull mode that reduces changes.Therefore, have dull increase of its signal level or the dull characteristic that reduces, then can be evaluated as this edge and possibly comprise chromatic aberation if be judged as detected edge.This has produced and has prevented in wide zone, slowly changing but the quilt that does not have chromatic aberation of local marked change is taken the photograph the effect of the false judgment of body.
In step S204, carry out axle to the edge that is be evaluated as the edge that possibly comprise chromatic aberation and go up the chromatic aberation evaluation.Carry out the dull increase/minimizing of signal level to the R in the fringe region, G and B plane and judge, and measure the fuzzy quantity on each plane.Fuzzy quantity is that signal level increases or dull minimizing mode continually varying distance with dullness in contiguous pixels.Because R, G and one of B plane have with all the other planes on the remarkable different fuzzy quantity of fuzzy quantity, thereby generate axle and go up a chromatic aberation.On the other hand, if all planes have fuzzy quantity much at one, then detected edge is likely normal edge or only comprises the edge of multiplying power chromatic aberation.Therefore, the edge that satisfies following two conditions is evaluated as the edge that comprises a last chromatic aberation.
(1) at least one plane has the fuzzy quantity that is equal to or greater than as the fuzzy quantity Th2 of threshold value in the planes of color at the detected edge of formation.
(2) forming in the planes of color at detected edge another plane at least has less than the fuzzy quantity as the fuzzy quantity Th2 of threshold value.
In the example shown in Fig. 7 B, all R on the edge 1, G and B plane have the fuzzy quantity less than fuzzy quantity Th2, thereby edge 1 is evaluated as the edge that does not comprise a last chromatic aberation probably.In addition, R on the edge 2 and G plane have the fuzzy quantity less than fuzzy quantity Th2, and the B plane on the edge 2 has the fuzzy quantity greater than fuzzy quantity Th2, thereby edge 2 is evaluated as the edge that comprises a last chromatic aberation probably.Through above-mentioned evaluation, can whether distinguish the edge according to the existence of chromatic aberation on the axle.
In step S205, from step S201, get rid of detected edge among the step S204 in the detected edge group, and the edge that will not be excluded remains the edge that the misalignment amount is obtained usefulness.
Edge detecting step S101 more than has been described.By this way, can not only also comprise that through eliminating the edge of a last chromatic aberation improves the misalignment amount and obtains precision through normal rim detection.
In step S206, on each remaining edge part, obtain the misalignment amount.In step S207, generate the multiplying power chromatic aberation correction data of the relation between presentation video height and the misalignment amount according to the picture altitude of misalignment amount of being obtained and appropriate section.In step S208, use multiplying power chromatic aberation correction data to proofread and correct the multiplying power chromatic aberation.At last, in step S209, chromatic aberation on the axis calibration.Although can use several kinds of axle colouring aberration correcting methods, the common use for example reduced the upward method of the aberration of the pixel of chromatic aberation of axle that generates.For example, in the time will being aberration, only need proofreading and correct and generate the signal level that axle is gone up the pixel of chromatic aberation, to reduce the value of this aberration to the value defined of Y-R and Y-B or G-R and G-B acquisition.
Although will in contiguous pixels, with the judgement that dullness increases or dull minimizing mode continually varying distance definition is a fuzzy quantity chromatic aberation edge extracting unit 51 on the axle be described as an example by signal level through adopting, the invention is not restricted to this.
In zone, through the gradient ratio of following each pixel of calculating with edge for example shown in Figure 8:
GradRatioBG＝ΔB/ΔG
GradRatioRG＝ΔR/ΔG
Through following compute gradient Δ B:
ΔB
i＝|B
i-1-B
i+1|
Wherein, B
iBe the signal level of interested pixel, and B
I-1And B
I+1Be and have signal level B
iThe signal level of pixel pixel adjacent.Calculate Δ R and Δ G through similar calculation equation.The interval judgement that the gradient ratio that will calculate with above-mentioned equality continues to surpass the pixel of threshold value Th3 is a fuzzy quantity.Because a plane in R, G and the B plane have with all the other planes on the remarkable different fuzzy quantity of fuzzy quantity, go up a chromatic aberation so generate axle.On the other hand, if all planes have fuzzy quantity much at one, then detected edge is likely normal edge or only comprises the edge of multiplying power chromatic aberation.Therefore, the edge that satisfies following two conditions is judged as the edge that comprises a last chromatic aberation.
(1) at least one plane has the fuzzy quantity that is equal to or greater than as the fuzzy quantity Th3 of threshold value in the planes of color at the detected edge of formation.
(2) forming in the planes of color at detected edge another plane at least has less than the fuzzy quantity as the fuzzy quantity Th3 of threshold value.
In example shown in Figure 8, all R on the edge 1, G and B plane have the fuzzy quantity less than fuzzy quantity Th3, thereby edge 1 is evaluated as the edge that does not comprise a last chromatic aberation probably.In addition, R on the edge 2 and G plane have the fuzzy quantity less than fuzzy quantity Th3, and the B plane on the edge 2 has the fuzzy quantity greater than fuzzy quantity Th3, thereby edge 2 is evaluated as the edge that comprises a last chromatic aberation probably.Through above-mentioned evaluation, can whether distinguish the edge according to the existence of chromatic aberation on the axle.
Although more than specified the preferred embodiments of the present invention, the invention is not restricted to these specific embodiments, and can under the situation that does not deviate from scope of the present invention, comprise various patterns in the present invention.And, can make up some embodiment in the foregoing description as required.
Other embodiment
Can also utilize read and the program of executive logging on storage arrangement with the computer (perhaps device such as CPU or MPU) of the system or equipment of the function of carrying out the foregoing description and through following method realize of the present invention aspect; Wherein, the computer that utilizes system or equipment is through for example reading and the program of executive logging on storage arrangement carried out the step of said method with the function of carrying out the foregoing description.For this reason, for example, this program is offered computer through network or through various types of recording mediums (for example, computer-readable medium) as storage arrangement.
Although the present invention has been described with reference to exemplary embodiments, should be appreciated that, the invention is not restricted to disclosed exemplary embodiments.The scope of appended claims meets the wideest explanation, to comprise all this type modifications, equivalent structure and function.
Claims (6)
1. image processing equipment comprises:
Edge detection unit is used for from by detecting the edge with the formed view data of the corresponding signal of multiple color;
Chromatic aberation edge detection unit on the axle is used for being judged as the edge that comprises a last chromatic aberation from the detection of said edge;
Misalignment amount acquiring unit is used to obtain the misalignment amount on the edge; And
Correcting unit is used to use the correcting value based on said misalignment amount to carry out the chromatic aberation correction,
Wherein, It is to comprise that said axle goes up the edge of chromatic aberation with following rim detection that said axle is gone up the chromatic aberation edge detection unit: have the fuzzy quantity of the threshold value of being not less than with the corresponding signal of at least a color on this edge of said view data; And have fuzzy quantity with the corresponding signal of another kind of at least color on this edge of said view data less than said threshold value, and
Said misalignment amount acquiring unit from by the detected edge of said edge detection unit, with go up different edge, the detected edge of chromatic aberation edge detection unit by said axle and obtain said misalignment amount.
2. image processing equipment according to claim 1; It is characterized in that; Said misalignment amount acquiring unit based on signal level on each edge and the corresponding signal of a kind of color and and the signal level of the corresponding signal of other color between the summation of difference, obtain said misalignment amount.
3. image processing equipment according to claim 1 is characterized in that, said fuzzy quantity is that signal level increases with dullness or the dull mode continually varying distance that reduces in contiguous pixels.
4. image processing equipment according to claim 1 is characterized in that, is provided with to each imaging conditions in a plurality of imaging conditions that keep in advance and estimates the said threshold value that said axle is gone up chromatic aberation institute basis.
5. image processing equipment according to claim 4 is characterized in that, said imaging conditions comprise employed pick-up lens when generating said view data type, taken the photograph at least one in body distance, pupil distance, F value and the focal length.
6. image processing method may further comprise the steps:
Use edge detection unit from by detecting the edge with the formed view data of the corresponding signal of multiple color;
The chromatic aberation edge detection unit that goes up the use axle detects from said edge and is judged as the edge that comprises a last chromatic aberation;
Use misalignment amount acquiring unit to obtain the misalignment amount on the edge; And
The utilization of use correcting unit is carried out the chromatic aberation correction based on the correcting value of said misalignment amount,
Wherein, It is to comprise that said axle goes up the edge of chromatic aberation with following rim detection that said axle is gone up the chromatic aberation edge detection unit: have the fuzzy quantity of the threshold value of being not less than with the corresponding signal of at least a color on this edge of said view data; And have fuzzy quantity with the corresponding signal of another kind of at least color on this edge of said view data less than said threshold value, and
Said misalignment amount acquiring unit from by the detected edge of said edge detection unit, with go up different edge, the detected edge of chromatic aberation edge detection unit by said axle and obtain said misalignment amount.
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| JP2011035177 | 2011-02-21 | ||
| JP2011-035177 | 2011-02-21 | ||
| JP2012013430A JP5840008B2 (en) | 2011-02-21 | 2012-01-25 | Image processing apparatus, image processing method, and program |
| JP2012-013430 | 2012-01-25 |
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| US (1) | US8736737B2 (en) |
| EP (1) | EP2490174A3 (en) |
| JP (1) | JP5840008B2 (en) |
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Also Published As
| Publication number | Publication date |
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| US8736737B2 (en) | 2014-05-27 |
| CN102685511B (en) | 2014-09-03 |
| US20120212644A1 (en) | 2012-08-23 |
| EP2490174A2 (en) | 2012-08-22 |
| KR101368715B1 (en) | 2014-03-04 |
| EP2490174A3 (en) | 2017-11-22 |
| JP5840008B2 (en) | 2016-01-06 |
| KR20120095791A (en) | 2012-08-29 |
| JP2012191607A (en) | 2012-10-04 |
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